Triple
T37547109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wahba problem in spline smoothing |
E933493
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | nonparametric regression method |
C65258
|
CONCEPT FINISHED |
How this triple was built (1 step)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: nonparametric regression method Context triple: [Wahba problem in spline smoothing, instanceOf, nonparametric regression method]
-
A.
nonparametric test
A nonparametric test is a statistical hypothesis test that does not assume a specific distribution for the population and instead relies on the ranks or signs of the data.
-
B.
seminal work in nonparametric statistics
A seminal work in nonparametric statistics is a foundational contribution that introduces or rigorously develops distribution-free methods for inference, estimation, or testing, significantly shaping subsequent theory and applications in the field.
-
C.
nonperturbative method
A nonperturbative method is a theoretical or computational approach that captures the full behavior of a system without relying on expansions in a small parameter, allowing it to describe strong-coupling or highly nonlinear regimes where perturbation theory fails.
-
D.
nonlinear function
A nonlinear function is a mathematical relationship between variables in which the rate of change is not constant, so its graph does not form a straight line.
-
E.
stochastic approximation method
A stochastic approximation method is an iterative algorithmic technique for finding roots or optima of functions when only noisy or sample-based observations are available, updating estimates using random data to converge to the desired solution.
- F. None of above. chosen
Provenance (1 batch)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f76eca55bc8190acf25741793d5dac |
completed | May 3, 2026, 3:50 p.m. |
Created at: May 3, 2026, 4:17 p.m.